Abstract: Several recent research efforts in biometrics have focused on developing the touchless fingerprint identification system. Most of them are using imaging resulting from cameras and mobile devices. The acquired images are firstly subjected to robust preprocessing steps to localise region of interest in order to extract its features. In the literature, touchless fingerprint features are generally based on algorithms designed for minutiae analysis in touch-based images. Because of perspective distortions and deformations in the samples, minutiae-based techniques can obtain poor results. This paper investigates multi-resolution decomposition features to overcome the limitations of using traditional minutiae algorithms in term of accuracy and matching speed. These decompositions are implemented on Hong Kong Polytechnic University 2D touchless fingerprint database that contains 10,080 images. Experimental results illustrate successful use of undecimated discrete wavelet transform (UDWT) and discrete wavelet packet transform (DWPT) which give better performance than discrete wavelet transform (DWT) and minutiae-based method with less calculation cost.